Evidence map›Paper›PMID 36566319›Full record

ArticleHeredity2023

Predicting recombination frequency from map distance.

Mikko Kivikoski, Pasi Rastas, Ari Löytynoja, Juha Merilä

Abstract read
In one paragraph

Article in Heredity, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

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0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  7. De Novo Mutation Rates in Sticklebacks.Molecular biology and evolution · 2023
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Mikko KivikoskiEcological Genetics Research Unit, Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, FI-00014, Finland. mikko.kivikoski@helsinki.fi.ORCID 0000-0001-7105-651X
Pasi RastasInstitute of Biotechnology, HiLIFE, University of Helsinki, Helsinki, FI-00014, Finland.ORCID 0000-0003-2768-1339
Ari LöytynojaInstitute of Biotechnology, HiLIFE, University of Helsinki, Helsinki, FI-00014, Finland.ORCID 0000-0001-5389-6611
Juha MeriläEcological Genetics Research Unit, Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, FI-00014, Finland.ORCID 0000-0001-9614-0072

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Map distance is one of the key measures in genetics and indicates the expected number of crossovers between two loci. Map distance is estimated from the observed recombination frequency using mapping functions, the most widely used of those, Haldane and Kosambi, being developed at the time when the number of markers was low and unobserved crossovers had a substantial effect on the recombination fractions. In contemporary high-density marker data, the probability of multiple crossovers between adjacent loci is negligible and different mapping functions yield the same result, that is, the recombination frequency between adjacent loci is equal to the map distance in Morgans. However, high-density linkage maps contain an interpretation problem: the map distance over a long interval is additive and its association with recombination frequency is not defined. Here, we demonstrate with high-density linkage maps from humans and stickleback fishes that the inverses of Haldane's and Kosambi's mapping functions systematically underpredict recombination frequencies from map distance. To remedy this, we formulate a piecewise function that yields more accurate predictions of recombination frequency from map distance. Our results demonstrate that the association between map distance and recombination frequency is context-dependent and without a universal solution.

Indexed as

Recombination, GeneticChromosome MappingGenetic LinkageHumansProbability

Identifiers

PMID36566319
PMCPMC9981558

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.